The massive and exponential growth of genomic, structural, biochemical and clinical data on the human kinome poses major challenges in using existing data for cancer and clinical research. Here we describe an ontological framework for integrating and conceptualizing diverse forms of protein kinase data in a machine readable, human understandable form. We demonstrate the utility of this framework in mining the cancer kinome and in generating testable hypotheses for experimental studies. Through the iterative process of aggregate ontology querying, hypothesis generation and experimental validation, we identify novel mutational hotspots in key regulatory regions of the kinase domain, and demonstrate the impact of identified mutations on kinase activity and drug sensitivity. We find that mutations mapping to the regulatory spine activate the kinase domain through distinct mechanisms and contribute to drug resistance. User‐friendly tools to mine cancer mutations in the context of naturally occurring variants, pathways, and drug sensitivity profiles will be discussed.Support or Funding InformationNIH RO1 GM 11409‐01
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